Browsing by Subject "Liquid chromatography"

Now showing 1 - 7 of 7
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    A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer's disease
    (Springer Nature, 2023-04-14) Merrihew, Gennifer E.; Park, Jea; Plubell, Deanna; Searle, Brian C.; Keene, C. Dirk; Larson, Eric B.; Bateman, Randall; Perrin, Richard J.; Chhatwal, Jasmeer P.; Farlow, Martin R.; McLean, Catriona A.; Ghetti, Bernardino; Newell, Kathy L.; Frosch, Matthew P.; Montine, Thomas J.; MacCoss, Michael J.; Neurology, School of Medicine
    Alzheimer's disease (AD) is a looming public health disaster with limited interventions. Alzheimer's is a complex disease that can present with or without causative mutations and can be accompanied by a range of age-related comorbidities. This diverse presentation makes it difficult to study molecular changes specific to AD. To better understand the molecular signatures of disease we constructed a unique human brain sample cohort inclusive of autosomal dominant AD dementia (ADD), sporadic ADD, and those without dementia but with high AD histopathologic burden, and cognitively normal individuals with no/minimal AD histopathologic burden. All samples are clinically well characterized, and brain tissue was preserved postmortem by rapid autopsy. Samples from four brain regions were processed and analyzed by data-independent acquisition LC-MS/MS. Here we present a high-quality quantitative dataset at the peptide and protein level for each brain region. Multiple internal and external control strategies were included in this experiment to ensure data quality. All data are deposited in the ProteomeXchange repositories and available from each step of our processing.
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    Chemical Assay for the Detection of Vertebrate Fecal Metabolites in Adult Blow Flies (Diptera: Calliphoridae)
    (Oxford, 2018-06-06) Owings, Charity G.; Skaggs, Christine; Sheriff, Winyu; Manicke, Nicholas; Picard, Christine J.; Department of Biology, School of Science
    Filth flies are commonly implicated in pathogen transmission routes due to their affinity for vertebrate waste and their synanthropic associations. However, solidifying the link between flies and infected feces in the wild can be difficult, as interpretations made solely from microbial culturing or sequencing methods may represent an incomplete picture of pathogen acquisition. We present an analytical assay using high performance liquid chromatography tandem mass spectrometry (HPLC MS/MS) to detect vertebrate fecal metabolites (urobilinoids) in adult blow fly guts. Proof of concept experiments consisted of controlled feeding in which flies were grouped into three treatments (unfed, exposure to beef liver tissue, and exposure to canine feces; N = 20/treatment) using the black blow fly Phormia regina Meigen (Diptera: Calliphoridae). It was revealed that only feces-related samples exhibited peaks with an m/z of 591 and MS/MS spectra consistent with urobilinoids. These peaks were not seen for beef liver tissue, flies exposed to beef liver tissue, or unfed flies. Samples taken directly from beef liver tissue and from feces of several animals were also tested. To test this assay in wild flies, 216 flies were additionally analyzed to determine whether they had ingested vertebrate feces. About 13% of the wild flies exhibited these same peaks, providing a baseline measure of blow flies collected in urban and residential areas consuming feces from the environment. Overall, this assay can be used for P. regina collected in an applied setting and its integration with microbial culturing and sequencing methods will help to improve its use.
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    Combining NMR and LC/MS Using Backward Variable Elimination: Metabolomics Analysis of Colorectal Cancer, Polyps, and Healthy Controls
    (ACS Publications, 2016-08-16) Deng, Lingli; Gu, Haiwei; Zhu, Jiangjiang; Gowda, G. A. Nagana; Djukovic, Danijel; Chiorean, Gabriela; Raftery, Daniel; Department of Medicine, School of Medicine
    Both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) play important roles in metabolomics. The complementary features of NMR and MS make their combination very attractive; however, currently the vast majority of metabolomics studies use either NMR or MS separately, and variable selection that combines NMR and MS for biomarker identification and statistical modeling is still not well developed. In this study focused on methodology, we developed a backward variable elimination partial least-squares discriminant analysis algorithm embedded with Monte Carlo cross validation (MCCV-BVE-PLSDA), to combine NMR and targeted liquid chromatography (LC)/MS data. Using the metabolomics analysis of serum for the detection of colorectal cancer (CRC) and polyps as an example, we demonstrate that variable selection is vitally important in combining NMR and MS data. The combined approach was better than using NMR or LC/MS data alone in providing significantly improved predictive accuracy in all the pairwise comparisons among CRC, polyps, and healthy controls. Using this approach, we selected a subset of metabolites responsible for the improved separation for each pairwise comparison, and we achieved a comprehensive profile of altered metabolite levels, including those in glycolysis, the TCA cycle, amino acid metabolism, and other pathways that were related to CRC and polyps. MCCV-BVE-PLSDA is straightforward, easy to implement, and highly useful for studying the contribution of each individual variable to multivariate statistical models. On the basis of these results, we recommend using an appropriate variable selection step, such as MCCV-BVE-PLSDA, when analyzing data from multiple analytical platforms to obtain improved statistical performance and a more accurate biological interpretation, especially for biomarker discovery. Importantly, the approach described here is relatively universal and can be easily expanded for combination with other analytical technologies.
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    Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry
    (American Chemical Society, 2024-06-04) Jiang, Yuming; Rex, Devasahayam Arokia Balaya; Schuster, Dina; Neely, Benjamin A.; Rosano, Germán L.; Volkmar, Norbert; Momenzadeh, Amanda; Peters-Clarke, Trenton M.; Egbert, Susan B.; Kreimer, Simion; Doud, Emma H.; Crook, Oliver M.; Yadav, Amit Kumar; Vanuopadath, Muralidharan; Hegeman, Adrian D.; Mayta, Martín L.; Duboff, Anna G.; Riley, Nicholas M.; Moritz, Robert L.; Meyer, Jesse G.; Biochemistry and Molecular Biology, School of Medicine
    Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.
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    Deep Intact Proteoform Characterization in Human Cell Lysate using High-pH and Low-pH Reversed-Phase Liquid Chromatography
    (American Chemical Society, 2019-12) Yu, Dahang; Wang, Zhe; Sutton, Kellye A.; Liu, Xiaowen; Wu, Si; Computer and Information Science, School of Science
    Post-translational modifications (PTMs) play critical roles in biological processes and have significant effects on the structures and dynamics of proteins. Top-down proteomics methods were developed for and applied to the study of intact proteins and their PTMs in human samples. However, the large dynamic range and complexity of human samples makes the study of human proteins challenging. To address these challenges, we developed a 2D pH RP/RPLC-MS/MS technique that fuses high-resolution separation and intact protein characterization to study the human proteins in HeLa cell lysate. Our results provide a deep coverage of soluble proteins in human cancer cells. Compared to 225 proteoforms from 124 proteins identified when 1D separation was used, 2778 proteoforms from 628 proteins were detected and characterized using our 2D separation method. Many proteoforms with critically functional PTMs including phosphorylation were characterized. Additionally, we present the first detection of intact human GcvH proteoforms with rare modifications such as octanoylation and lipoylation. Overall, the increase in the number of proteoforms identified using 2DLC separation is largely due to the reduction in sample complexity through improved separation resolution, which enables the detection of low abundance PTM modified proteoforms. We demonstrate here that 2D pH RP/RPLC is an effective technique to analyze complex protein samples using top-down proteomics.
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    Fast and high-throughput LC-MS characterization, and peptide mapping of engineered AAV capsids using LC-MS/MS
    (Elsevier, 2022-09-24) Lam, Anh K.; Zhang, Junping; Frabutt, Dylan; Mulcrone, Patrick L.; Li, Lei; Zeng, Lifan; Herzog, Roland W.; Xiao, Weidong; Pediatrics, School of Medicine
    Adeno-associated virus (AAV) has emerged as a leading platform for gene therapy. With the skyrocketing rate of AAV research and the prevalence of many new engineered capsids being investigated in preclinical and clinical trials, capsid characterization plays a vital role in serotype confirmation and quality control. Further, peptide mapping the capsid proteins might inevitably be a future requirement by regulatory agencies since it is a critical step in good manufacturing practice (GMP) for biotherapeutic characterization. To overcome many challenges that traditional methods like SDS-PAGE and western blots carry, liquid chromatography and mass spectrometry (LC-MS) allows high resolution and sensitivity with great accuracy in characterizing the AAV capsid proteins. Our optimized LC-MS method provides quick sample preparation, a fast and high-throughput 4-min run, and high sensitivity, which allows for very efficient characterization of wild-type and engineered capsids. This study also reports the usage of LC-MS/MS peptide mapping of AAV capsid proteins to determine the most accessible lysine residues targeted by chemical modifications. Our detailed protocols are anticipated to promote the development and discovery of AAV variants with high accuracy and efficiency.
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    Quantitative Top-Down Proteomics in Complex Samples Using Protein-Level Tandem Mass Tag Labeling
    (American Chemical Society, 2021-06-02) Yu, Dahang; Wang, Zhe; Cupp-Sutton, Kellye A.; Guo, Yanting; Kou, Qiang; Smith, Kenneth; Liu, Xiaowen; Wu, Si; BioHealth Informatics, School of Informatics and Computing
    Labeling approaches using isobaric chemical tags (e.g., isobaric tagging for relative and absolute quantification, iTRAQ and tandem mass tag, TMT) have been widely applied for the quantification of peptides and proteins in bottom-up MS. However, until recently, successful applications of these approaches to top-down proteomics have been limited because proteins tend to precipitate and “crash” out of solution during TMT labeling of complex samples making the quantification of such samples difficult. In this study, we report a top-down TMT MS platform for confidently identifying and quantifying low molecular weight intact proteoforms in complex biological samples. To reduce the sample complexity and remove large proteins from complex samples, we developed a filter-SEC technique that combines a molecular weight cutoff filtration step with high-performance size exclusion chromatography (SEC) separation. No protein precipitation was observed in filtered samples under the intact protein-level TMT labeling conditions. The proposed top-down TMT MS platform enables high-throughput analysis of intact proteoforms, allowing for the identification and quantification of hundreds of intact proteoforms from Escherichia coli cell lysates. To our knowledge, this represents the first high-throughput TMT labeling-based, quantitative, top-down MS analysis suitable for complex biological samples.